Building Regularization¶

Install package¶

To use the geoai-py package, ensure it is installed in your environment. Uncomment the command below if needed.

In [1]:

# %pip install geoai-py

# %pip install geoai-py

Import package¶

In [2]:

import geoai

import geoai

Download sample data¶

In [3]:

raster_url = "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_building_masks.tif"

raster_url = "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_building_masks.tif"

In [4]:

raster_path = geoai.download_file(raster_url)

raster_path = geoai.download_file(raster_url)

naip_building_masks.tif:   0%|          | 0.00/61.6k [00:00<?, ?B/s]

naip_building_masks.tif: 100%|██████████| 61.6k/61.6k [00:00<00:00, 9.42MB/s]

In [5]:

geoai.view_image(raster_path, figsize=(18, 10))

geoai.view_image(raster_path, figsize=(18, 10))

Convert raster to vector¶

In [6]:

gdf = geoai.raster_to_vector(raster_path, output_path="naip_building_masks.geojson")

gdf = geoai.raster_to_vector(raster_path, output_path="naip_building_masks.geojson")

INFO:pyogrio._io:Created 677 records

Vectorized data saved to naip_building_masks.geojson

In [7]:

geoai.view_vector_interactive(
    gdf, style_kwds={"color": "blue", "fillOpacity": 0}, tiles="Satellite"
)

geoai.view_vector_interactive( gdf, style_kwds={"color": "blue", "fillOpacity": 0}, tiles="Satellite" )

Out[7]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Building regularization¶

In [8]:

gdf_regularized = geoai.regularize_building_footprints(
    building_polygons=gdf,
    angle_tolerance=10,
    simplify_tolerance=0.5,
    orthogonalize=True,
    preserve_topology=True,
)

gdf_regularized = geoai.regularize_building_footprints( building_polygons=gdf, angle_tolerance=10, simplify_tolerance=0.5, orthogonalize=True, preserve_topology=True, )

In [9]:

geoai.view_vector_interactive(
    gdf_regularized, style_kwds={"color": "red", "fillOpacity": 0}, tiles="Satellite"
)

geoai.view_vector_interactive( gdf_regularized, style_kwds={"color": "red", "fillOpacity": 0}, tiles="Satellite" )

Out[9]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Hybrid regularization¶

In [10]:

gdf_hybrid = geoai.hybrid_building_regularization(gdf)

gdf_hybrid = geoai.hybrid_building_regularization(gdf)

In [11]:

geoai.view_vector_interactive(
    gdf_hybrid, style_kwds={"color": "green", "fillOpacity": 0}, tiles="Satellite"
)

geoai.view_vector_interactive( gdf_hybrid, style_kwds={"color": "green", "fillOpacity": 0}, tiles="Satellite" )

Out[11]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Adaptive regularization¶

In [12]:

gdf_adaptive = geoai.adaptive_building_regularization(
    building_polygons=gdf,
    simplify_tolerance=0.5,
    area_threshold=0.9,
    preserve_shape=True,
)

gdf_adaptive = geoai.adaptive_building_regularization( building_polygons=gdf, simplify_tolerance=0.5, area_threshold=0.9, preserve_shape=True, )

In [13]:

geoai.view_vector_interactive(
    gdf_adaptive, style_kwds={"color": "yellow", "fillOpacity": 0}, tiles="Satellite"
)

geoai.view_vector_interactive( gdf_adaptive, style_kwds={"color": "yellow", "fillOpacity": 0}, tiles="Satellite" )

Out[13]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Compare regularization methods¶

In [14]:

import leafmap.foliumap as leafmap

import leafmap.foliumap as leafmap

In [15]:

m = leafmap.Map()
m.add_basemap("SATELLITE")
m.add_gdf(gdf, layer_name="Original")
m.add_gdf(
    gdf_regularized, style={"color": "red", "fillOpacity": 0}, layer_name="Regularized"
)
m.add_gdf(gdf_hybrid, style={"color": "green", "fillOpacity": 0}, layer_name="Hybrid")
m.add_gdf(
    gdf_adaptive, style={"color": "yellow", "fillOpacity": 0}, layer_name="Adaptive"
)
legend = {
    "Original": "blue",
    "Regularized": "red",
    "Hybrid": "green",
    "Adaptive": "yellow",
}
m.add_legend(title="Building Footprints", legend_dict=legend)
m

m = leafmap.Map() m.add_basemap("SATELLITE") m.add_gdf(gdf, layer_name="Original") m.add_gdf( gdf_regularized, style={"color": "red", "fillOpacity": 0}, layer_name="Regularized" ) m.add_gdf(gdf_hybrid, style={"color": "green", "fillOpacity": 0}, layer_name="Hybrid") m.add_gdf( gdf_adaptive, style={"color": "yellow", "fillOpacity": 0}, layer_name="Adaptive" ) legend = { "Original": "blue", "Regularized": "red", "Hybrid": "green", "Adaptive": "yellow", } m.add_legend(title="Building Footprints", legend_dict=legend) m

Out[15]: